Yiran Li report

Basic plot

Load data from CSV

library(ggplot2)
super_data_set = read.csv("super_data.csv", header = TRUE)
super_data_set$start_time = as.POSIXct(super_data_set$start_time, format='00%m-%d-%y %H:%M:%S')

Scatterplot

qplot(super_data_set$Region,super_data_set$duration,main = "Basic plot for Region type against Duration",xlab = "region", ylab = "Duration")

Text

ggplot(super_data_set[1:100,], aes(super_data_set[1:100,]$Region, super_data_set[1:100,]$start_time)) + labs(x = "Region") + labs(y = "Start time") + geom_text(aes(label = super_data_set[1:100,]$duration))

Bar chart

ggplot(super_data_set, aes(super_data_set$Region)) + geom_bar()+labs(x = "Region")

Line chart

ggplot(super_data_set, aes(super_data_set$start_time, super_data_set$duration)) + geom_line() +labs(x = "Start time")+labs(y = "Duration")

Area chart

ggplot(super_data_set[1:1000,], aes(super_data_set[1:1000,]$start_time, super_data_set[1:1000,]$duration)) + geom_area() +labs(x = "Start time")+labs(y = "Duration")

Dot plot

ggplot(super_data_set, aes(x = super_data_set$duration)) + geom_dotplot(binwidth = 20) +labs(x = "Duration")

Histogram

ggplot(super_data_set, aes(x = super_data_set$start_time)) + geom_histogram(binwidth = 3600) + labs(x = "Start time")

Frequency polygon

ggplot(super_data_set, aes(x = super_data_set$start_time)) + geom_freqpoly(color = "blue")+ labs(x = "Start time")

Box plot

ggplot(super_data_set, aes(super_data_set$passholder_type, super_data_set$start_time)) + geom_boxplot() + labs(x = "Passholder type") + labs(y = "Start time")

Violin plot

ggplot(super_data_set, aes(super_data_set$passholder_type, super_data_set$start_time)) + geom_violin() + labs(x = "Passholder type") + labs(y = "Start time")

Facets

ggplot(super_data_set, aes(super_data_set$passholder_type, 
                                                      super_data_set$start_time, 
                                                      color = super_data_set$Region)) +
  geom_point() +
  facet_grid(cols=vars(super_data_set$Region)) +  
  theme(legend.position="none",axis.text.x = element_text(angle = 90, hjust = 1)) +
  labs(x = "Pass holder type") +
  labs(y = "Start time")

GGMAP

1. Load the data

library(ggmap)

Google Maps API Terms of Service: http://developers.google.com/maps/terms.
Please cite ggmap if you use it: see citation("ggmap") for details.

#source('register_google.R') 
register_google(key = "AIzaSyAfNEsW1TDQ8hGEbnpQsBJWZZEFoxHzZh4")
googlemap.ca <- get_googlemap(c(-122.796161,37.1931243), zoom = 6)

Source : https://maps.googleapis.com/maps/api/staticmap?center=37.193124,-122.796161&zoom=6&size=640x640&scale=2&maptype=terrain&key=AIzaSyAfNEsW1TDQ8hGEbnpQsBJWZZEFoxHzZh4

ggmap(googlemap.ca)

2. Draw stations on the map

#map.google <- get_map(c(lon=-118.456667, lat=34.010167), zoom = 12)
#plot(station_data)
#ggmap(map.google) +
#  geom_point(data = station_data, aes(x = station_data$features, y = lat, color=alt), alpha = 0.5, shape=1) +
#  scale_colour_gradient(limits=c(4000, 8000), low="red", high="blue")

Interactive graph

1. load data

library(plotly)
super_data_set$text = paste('Duration: ',  super_data_set$duration, '<br>Region: ', super_data_set$Region)
#g = qplot(
 # passholder_type,
  #duration,
  #data = duration_passholder_type_100,
  #main = "Basic plot for Passholder type against duration",
  #xlab = "pass holder tpye", 
  #ylab = "duration", aes(text = text)) 
g = qplot(super_data_set$Region,super_data_set$duration,color=factor(super_data_set$Region),main = "Basic plot for Region type against Duration",xlab = "region", ylab = "Duration",  aes(text = super_data_set$text)) + geom_jitter()

Ignoring unknown aesthetics: text

ggplotly()